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Author

Nima Rahmati

4 papers indexed here

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Adaptive privacy-preserving federated learning framework for real-time cybersecurity threat detection in distributed IoT networks

This paper presents an innovative Adaptive Privacy-Preserving Federated Learning framework specifically designed for real-time cybersecurity threat detection in distributed IoT networks, offering a practical framework for real-world deployment in infrastructure-critical applications.

Milad Rahmati, Nima Rahmati · 0 citations
#reinforcement learning Open access Sep 2026

Dynamic federated multi-agent planning under partial observability and network instability for real-time edge applications

This paper introduces Dynamic Federated Multi-Agent Planning (DFMAP), a novel framework that integrates federated reinforcement learning (FRL) with partially observable Markov decision processes (POMDPs) for real-time decision-making in volatile edge environments.

Milad Rahmati, Nima Rahmati · 0 citations
#federated learning Open access Sep 2026

Adaptive model poisoning detection in federated learning for EV charging networks: a blockchain-anchored explainable AI approach

A novel adaptive detection framework that combines blockchain-based integrity verification with explainable artificial intelligence to identify and mitigate poisoning attempts in federated learning systems for electric vehicle charging networks is presented.

Milad Rahmati, Nima Rahmati · 0 citations
Open access Aug 2026

Post-quantum lightweight cryptographic algorithm for secure real-time decision-making in distributed optimization networks

The imminent threat posed by quantum computing to classical cryptographic systems necessitates the development of quantum-resistant, efficient, and scalable encryption techniques, especially for real-time distributed optimization networks critical to national infrastructure. This study introduces a novel lightweight po...

Milad Rahmati, Nima Rahmati · 0 citations

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